Development of a Predictive System for Customer Buying Pattern Using Apriori Algorithm

Abstract

A lot of retailers face the challenge of how to understand their customers’ buying habits, and this makes stocking products, arrange items on shelves, and making customers to come back again a difficult task. Without understanding what the customer typically wants to buy, retail stores can miss out on opportunities to increase sales and improve customer satisfaction. To address this, this study developed a system using the Apriori algorithm to analyze past shopping data from a supermarket. The developed system identifies patterns in the items of customers that are frequently bought together. This allows the business to predict future purchases. By using these method, stores can now manage their stock better to create better marketing strategies, and to improve their customers overall shopping experience. The results that were obtained from this study also show that the system can help businesses stay competitive by understanding customer needs and acting on them more effectively.